Visible to the public Audit-based efficient accountability for node misbehavior in wireless sensor network

TitleAudit-based efficient accountability for node misbehavior in wireless sensor network
Publication TypeConference Paper
Year of Publication2017
AuthorsBalaji, V. S., Reebha, S. A. A. B., Saravanan, D.
Conference Name2017 International Conference on IoT and Application (ICIOT)
ISBN Number978-1-5386-1698-7
KeywordsAd hoc networks, AMD, audit-based efficient accountability, Audit-based Misbehavior Detection, behavioral audits, composability, continuous packet droppers, cryptography, faulty nodes, Metrics, misbehaving nodes, mobile ad hoc networks, mobile ad-hoc networks, Monitoring, multichannel networks, multihop ad hoc networks, network accountability, network functions, network nodes, node behavior, node misbehavior, Peer-to-peer computing, pubcrawl, resilience, Resiliency, Routing, selective packet droppers, self-organized networks, spread spectrum communication, telecommunication network management, telecommunication network routing, Wireless Sensor Network, Wireless sensor networks
Abstract

Wireless sensor network operate on the basic underlying assumption that all participating nodes fully collaborate in self-organizing functions. However, performing network functions consumes energy and other resources. Therefore, some network nodes may decide against cooperating with others. Node misbehavior due to selfish or malicious reasons or faulty nodes can significantly degrade the performance of mobile ad-hoc networks. To cope with misbehavior in such self-organized networks, nodes need to be able to automatically adapt their strategy to changing levels of cooperation. The problem of identifying and isolating misbehaving nodes that refuses to forward packets in multi-hop ad hoc networks. a comprehensive system called Audit-based Misbehavior Detection (AMD) that effectively and efficiently isolates both continuous and selective packet droppers. The AMD system integrates reputation management, trustworthy route discovery, and identification of misbehaving nodes based on behavioral audits. AMD evaluates node behavior on a per-packet basis, without employing energy-expensive overhearing techniques or intensive acknowledgment schemes. AMD can detect selective dropping attacks even if end-to-end traffic is encrypted and can be applied to multi-channel networks.

URLhttps://ieeexplore.ieee.org/document/8073609/
DOI10.1109/ICIOTA.2017.8073609
Citation Keybalaji_audit-based_2017